Hugging Face· Platform

Run a vLLM Server on HF Jobs in One Command

You can spin up a private, OpenAI-compatible LLM endpoint on Hugging Face infrastructure with a single command — no servers to provision, no Kubernetes, pay-per-second. Once it's up, you can query it from your laptop, a notebook, or anywhere else. It's the quickest way to stand up a model for tests, evals, or batch generation. (If you're after a managed, production-ready service instead, that's what Inference Endpoints are for — more on when to pick which at the end.) Here's the whole thing end to end. Prerequisites A payment method or a positive prepaid credit balance (Jobs is billed per‑minute by hardware usage). huggingface_hub >= 1.20.0 : pip install -U "huggingface_hub>=1.20.0" . Logged in locally: hf auth login . Launch the server hf jobs run is docker run for HF infrastructure. We use the official vllm/vllm-openai image, ask for a GPU with --flavor , and expose vLLM's port with --expose : hf jobs run --flavor a10g-large --expose 8000 -- timeout 2h \ vllm/vllm-openai:latest \ …

Announced

26 Jun 2026 00:00 UTC